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1,579 results for “Baltics”
BSIOM Baltic Sea-Ice Ocean Model 1950-2022
<p>Daily temperature, dissolved oxygen and salinity concentration data from the <a name="_Hlk167710471"></a>Baltic Sea Ice Ocean Model (BSIOM) from 1950 to 2022. A detailed description of the equations and modifications made, necessary to adapt the model to the Baltic Sea, can be found in Lehmann et al. (see references below). The model is forced realistically using the ERA5 global re-analysis in the preliminary extension version back to 1950. The resolution of the original output from BSIOM is specified with vertical 60 levels, which enables to resolve the upper 100m by layers of 3 m thickness. The horizontal resolution of the model is 2.5km. The datasets here presented are divided into surface and bottom files. We calculated the sea surface temperature (SST) using the average values from the first three depth layers (upper nine meters), while the sea bottom temperature (SBT) was the average of the last three depth layers following the bathymetry of the Western Baltic Sea (lower nine meters). The values for dissolved oxygen and salinity concentration were calculated in the same manner. The data is spatially constrained to the area between 9° 45’ to 14° 45’ East and 53° 53’ to 56° 30’ North.</p> <p>In the datasets, the following data is available: </p> <ul> <li>Lat: latitude values in degrees (°)</li> <li>Long: longitude values in degrees (°)</li> <li>Depth: depth values (m). The surface file shows a constant value of 1.5, while the bottom file shows the maximum depth (m) for that pixel. To show the depth in reference to the sea-level reference (0 meters) the values should be multiplied by -1.</li> <li>temp: temperature (°C)</li> <li>SO: salinity (g/kg)</li> <li>O2: dissolved oxygen (ml/L-1)</li> <li>t: day of the year (YYYY-MM-DD)</li> <li>LongLat: string with the combination of longitute and latitude values (only for the bottom file)</li> <li>GridID: identification value for each set of coordinates (Long and Lat)</li> </ul>
Directional wave data collected by R/V Aranda in the Baltic Sea
<p>Data source: Finnish Meteorological Institute</p> <p>This is wave and meteorological data collected on board R/V Aranda in July 2015 in the Baltic Sea. Each netcdf-file contains the data and metadata from one station.</p> <p>The experimental setup is described in the paper: Björkqvist, J.-V., Pettersson, H., Drennan, W. M., and Kahma, K. K., 2019: A new inverse phase speed spectrum of nonlinear gravity wind waves, Journal of Geophysical Research: Oceans, 124, 6097–6119, DOI: 10.1029/2018JC014904</p>
Monitoring of the Vistula estuary into the Baltic Sea using Sentinel-2 data
<p>Senitnel-2 data and dedicated presentations were used during the Daily Animation. The aim of the exercise was to familiarize the participants with the structure of Senitnel-2 data and creating RGB compositions in SNAP and QGIS software.</p> <p>Links to the presentation:</p> <p>http://fabspace.pl/wp-content/uploads/2017/11/RGB-w-QGIS.pdf</p> <p>http://fabspace.pl/wp-content/uploads/2017/11/RGB-w-SNAP.pdf</p> <p> </p>
Baltic Sea shipborne Hyperspectral Reflectance data from 2016
<p>Hyperspectral Remote-sensing reflectance data collected by the Finnish Environment Institute (SYKE) within the BONUS FerryScope project, analysed (quality checks and spectral filtering) at the Plymouth Marine Laboratory. Methods initially described in:</p> <p>The data were collected from merchant vessels Finnmaid (Finnlines) and Transpaper (Transatlantic). This data set is limited to records for the year 2016. </p> <p>Field data collection and processing:</p> <p>Simis, S.G.H., & Olsson, J. (2013). Unattended processing of shipborne hyperspectral reflectance measurements. Remote Sensing of Environment, 135, 202–212</p> <p>Data quality control: </p> <p>Qin, P., Simis, S.G.H., & Tilstone, G.H. (2017). Radiometric validation of atmospheric correction for MERIS in the Baltic Sea based on continuous observations from ships and AERONET-OC. Remote Sensing of Environment, 200, 263-280</p> <p> </p> <p>Data specification</p> <p>lat, lon - geographical latitude/longitude coordinates in decimal degrees</p> <p>time - timestamp (date+time) in UTC following ISO 8601 notation. </p> <p>(The location and time fields correspond to the start of a measurement)</p> <p>Rrs_001_3233 .... Rrs_193_9536 - Remote-sensing reflectance (Rrs, units 1/sr). The sequential numbering (1-193) denotes band number, the last term is wavelength x 10 in nm. For example Rrs_001_3233 is the 1st band centred at 323.3 nm. The wavebands approximate the native resolution of the 3-sensor system (TriOS Ramses ARC + ACC units) used to collect radiance and irradiance spectra of the sea surface and sky. </p> <p>Contributions:</p> <p>Stefan Simis, Jenni Attila, Mikko Kervinen, Kari Kallio, Sampsa Koponen, Sakari Väkevä maintained the in situ system.</p> <p>Stefan Simis developed the code to process the (ir)radiance data to Remote-sensing reflectance.</p> <p>Mikko Kervinen and Stefan Simis maintained the operational processing system</p> <p>Ping Qin analysed multi-year observation records and developed quality-control filters</p> <p>Silvia Pardo and Gavin Tilstone analysed the data against satellite sensor records. </p>
Central Baltic EwE validation
<p>Dataset contains parameters for the Central Baltic EwE foodweb model along with forcing and validation data as well as model output. All metadata information is contained in ICES WGSAM REPORT 2016 (Annex 3). The report is uploaded with the data set or can be accessed at <a href="https://www.ices.dk/community/groups/Pages/WGSAM.aspx">https://www.ices.dk/community/groups/Pages/WGSAM.aspx</a></p>
Fig. 1 in A new species of Platypelochares from Baltic amber (Coleoptera: Limnichidae)
Fig. 1. Fourier transformed infrared spectra (FT-IR) of the amber piece. Note the "Baltic shoulder" between 1190–1280 cm-1 (arrow).
Figs 2–7 in A new species of Platypelochares from Baltic amber (Coleoptera: Limnichidae)
Figs 2–7.Amber inclusion of Platypelochares electricus sp. nov. 2 – amber piece with the studied specimen. 3–7 – morphological details of P. electricus: 3 – ventral view; 4 – detail of the tubercle row on the pronotum (indicated by an arrow); 5 – detail of the ventral side of prosternum and right hypomeron, with the excavation (indicated by an arrow); 6 – lateral view; 7 – metacoxa and first four abdominal ventrites (arrow – lateral articulation of the tarsi).
Fig. 3 in New Baltic amber leafhoppers representing the oldest Aphrodinae and Megophthalminae (Hemiptera, Cicadellidae)
Fig. 3. Brevaphrodella nigra sp. nov. ♂. A. Body in dorsal view. B. Face. C. Pro- and mesothoracic legs in ventral view. D-E. Metathoracic leg. D. Apical portion of femur, tibia, and tarsomeres, dorsolateral view. E. First tarsomere, ventral view. F. Subgenital plates, and valve, ventral view. Scale bars: A-D, F = 0.5 mm; E = 0.25 mm.
Fig. 2. A-F in New Baltic amber leafhoppers representing the oldest Aphrodinae and Megophthalminae (Hemiptera, Cicadellidae)
Fig. 2. A-F. Eomegopthalmus lithuaniensis sp. nov. ♀. A. Crown, pronotum, and mesonotum, dorsal view. B. Face, anteroventral view. C. Right forewing, lateral view. D. Prothoracic leg, lateral view. E. Metathoracic leg, dorsal view. F. Second valvulae of ovipositor, general lateral view. G-I. Xestocephalites balticus sp. nov. ♂. G. Face. H. Apical portion of femur, tibia, and first tarsomere of metathoracic leg, lateral view. I. Subgenital plates, ventral view. Scale bars: A-H = 1 mm; I = 0.5 mm.
Fig. 1 in New Baltic amber leafhoppers representing the oldest Aphrodinae and Megophthalminae (Hemiptera, Cicadellidae)
Fig. 1. Habitus in dorsal and ventral view. A-B. Eomegopthalmus lithuaniensis sp. nov. ♀. C-D. Xestocephalites balticus sp. nov. ♂. E-F. Brevaphrodella nigra sp. nov. ♂. Scale bars = 1 mm.
Figure 1 in First described fossil representatives of the parasitoid wasp taxa Asaphesinae n. n. and Eunotinae (Hymenoptera: Chalcidoidea: Pteromalidae sensu lato) from Eocene Baltic amber
Figure 1. (a–c) Coriotela lasallei n. gen., n. sp. holotype female: (a) Body, dorso-lateral; (b) Head, mesosoma, and anterior part of metasomal, lateral, frl = frenal groove, occ = occipital carina. (c) Fore wing, clv = clava, clavomeres numbered. (d,e) Butiokeras costae n. gen., n. sp. holotype male: (d) Body, dorso-lateral; (e) Body, ventro-lateral.
Measurement report: Characterization of uncertainties of fluxes and fuel sulfur content from ship emissions at the Baltic Sea
<p>This data submission is connected to a scientific paper submitted to<br> Atmospheric Chemistry and Physics ("Measurement report: Characterization of uncertainties of fluxes and fuel sulfur content from ship emissions at the Baltic Sea" by Walden et al.). It consists of measurement results conducted beside the ship routs at the Baltic Sea near Helsinki, Finland. The gaseous and particle concentrations were measured along with the meteorological parameters, and the fluxes were calculated by the micrometeorological methods. The content of sulfur in the marine fuel, FSC, used by the passing ships was also calculated. We paid attention to calculate the uncertainties of the measurement results, both for the fluxes and for the FSC.</p> <p>The released data of:<br> 1. Gases, particles and met data (SO<sub>2</sub>, NO, NO<sub>2</sub>, O<sub>3</sub>, CO<sub>2</sub>, and N<sub>tot</sub> (number concentration of nanoparticles) as minute values. </p> <p>Data_ACP_Fig4_acbd.xlsx.</p> <p> <br> 2. Size distribution of nanoparticles (number concentration of nanoparticles at size class). Data_ACP_Fig6.xlsx</p> <p> <br> 3. Profiles of 30 min averages of gases, nanoparticles and meteorological parameters (SO<sub>2</sub>, NO, NO<sub>2</sub>, O<sub>3</sub>, CO<sub>2</sub>, and N<sub>tot</sub> (number concentration of nanoparticles), wind direction and wind speed, friction velocity, stability parameter and Monin-Obukhov length. Calculated values of atmospheric turbulence parameters and calculated fluxes of CO2 and nanoparticles by gradient and/or eddy covariance method.</p> <p>Data_ACP_Fig8_abcd_Fig9_abcd.xlsx<br> <br> 4. CO2 fluxes by Eddy covariance method from land based and sea based measurements. Concentration of CO2 in seawater and in air.</p> <p>Data_ACP_Fig10_ab.xlsxEngl</p>
Mapping present and future predicted distribution patterns for a meso-grazer guild in the Baltic Sea
<p>Baltic Sea communities consisting of key and endemic species are threatened by climate change. Using Ecological niche modelling, we map predicted distribution patterns under recent and future climate change scenarios (2050) for a food-web consisting of a guild of meso-grazers (Idotea spp.), their host algae (Fucus vesiculosus and F. radicans) and their fish predator (Gasterosteus aculeatus). Brackish water species depend on two important abiotic factors: temperature and salinity. We assess which of these environmental factors determines the distribution limits of the grazers in the Baltic Sea today. For species in a semi-enclosed sea area such as the Baltic Sea, climate-induced changes may lead to dramatic food-web effects. We assess the consequences of the predicted climate-induced habitat range changes for this unique Baltic community.<br /> </p>
FIGURES 5 - 8. Habitus. 5 in Review of the Tertiary microbombyliids Diptera: Mythicomyiidae in Baltic, Bitterfeld, and Dominican amber
FIGURES 5 - 8. Habitus. 5. Glabellula brunnifrons, sp. n. (specimen DE- 001) 6. Glabellula grimaldii, sp. n. (specimen DR- 11 - 18). 7. Mythicomyia dominicana, sp. n. (specimen DR- 11 - 9). 8. Mythenteles baltica, sp. n., female habitus (specimen BE- 001).
FIGURES 4 – 6 in New Zopheridae (Coleoptera: Tenebrionoidea) from Baltic amber
FIGURES 4 – 6. Xylolaemus richardklebsi sp. nov., holotype: 4 — habitus, dorsal view; 5 — habitus, ventral view; 6 — habitus, lateral view.
FIGURES 1 – 3 in New Zopheridae (Coleoptera: Tenebrionoidea) from Baltic amber
FIGURES 1 – 3. Xylolaemus legalovi sp. nov., holotype: 1 — habitus, dorsal view; 2 — details of forebody, ventral view; 3 — habitus, ventral view.
FIGURES 7 – 9 in New Zopheridae (Coleoptera: Tenebrionoidea) from Baltic amber
FIGURES 7 – 9. Diodesma slipinskii sp. nov., holotype: 7 — habitus, dorsal view; 8 — habitus, ventral view; 9 — habitus, lateral view.
FIGURES 1 – 3 in New Zopheridae (Coleoptera: Tenebrionoidea) from Baltic amber
FIGURES 1 – 3. Xylolaemus legalovi sp. nov., holotype: 1 — habitus, dorsal view; 2 — details of forebody, ventral view; 3 — habitus, ventral view.
FIGURES 4 – 6 in New Zopheridae (Coleoptera: Tenebrionoidea) from Baltic amber
FIGURES 4 – 6. Xylolaemus richardklebsi sp. nov., holotype: 4 — habitus, dorsal view; 5 — habitus, ventral view; 6 — habitus, lateral view.
FIGURES 7 – 9 in New Zopheridae (Coleoptera: Tenebrionoidea) from Baltic amber
FIGURES 7 – 9. Diodesma slipinskii sp. nov., holotype: 7 — habitus, dorsal view; 8 — habitus, ventral view; 9 — habitus, lateral view.
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OpenNeuro
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